scikit-learn | DisamKB

scikit-learn

E17661

Python library machine learning library open-source software

scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.

Aliases (8)

Statements (51)

Predicate	Object
instanceOf	Python library → machine learning library → open-source software →
compatibleWith	pandas →
domain	data analysis → data mining → machine learning →
hasAPI	estimator interface →
hasConcept	ColumnTransformer → FeatureUnion → GridSearchCV → KMeans → LogisticRegression → OneHotEncoder → PCA → Pipeline → RandomForestClassifier → RandomizedSearchCV → SVC → StandardScaler → fit method → fit_transform method → predict method → scorer functions → train_test_split → transform method →
license	BSD 3-Clause License →
programmingLanguage	Python →
provides	classification algorithms → clustering algorithms → dimensionality reduction methods → model selection tools → preprocessing utilities → regression algorithms →
repositoryPlatform	GitHub →
supports	cross-validation → feature extraction → feature selection → hyperparameter tuning → model evaluation → pipeline construction → semi-supervised learning → supervised learning → unsupervised learning →
targetUsers	data scientists → machine learning practitioners → researchers →
uses	NumPy → SciPy → matplotlib →
writtenIn	Python →

Referenced by (17)

Subject (surface form when different)	Predicate
scikit-learn ("FeatureUnion") → scikit-learn ("StandardScaler") → scikit-learn ("OneHotEncoder") → scikit-learn ("RandomForestClassifier") →	hasConcept
ColumnTransformer → GridSearchCV → RandomizedSearchCV →	partOf
pandas →	commonlyUsedWith
PCA (scikit-learn) ("scikit-learn Pipeline") →	compatibleWith
KMeans →	implementedIn
SVC →	implementedInLibrary
NumPy →	influenced
GridSearchCV ("scikit-learn 0.16 or earlier") →	introducedInLibrary
ColumnTransformer ("scikit-learn 0.20") →	introducedInVersion
Python →	machineLearningLibrary
LogisticRegression ("sklearn.linear_model") →	module
LogisticRegression →	providedBy